1 citations · 2 across the 2 of their papers we have counts for
2 papers
eess.AS2023★ 1 cited
What Can an Accent Identifier Learn? Probing Phonetic and Prosodic Information in a Wav2vec2-based Accent Identification Model
Mu Yang, Ram C. M. C. Shekar, Okim Kang +1
This study is focused on understanding and quantifying the change in phoneme and prosody information encoded in the Self-Supervised Learning (SSL) model, brought by an accent ident…
eess.AS2022★ 1 cited
Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment
Mu Yang, Kevin Hirschi, Stephen D. Looney +2
Current leading mispronunciation detection and diagnosis (MDD) systems achieve promising performance via end-to-end phoneme recognition. One challenge of such end-to-end solutions…